Literature DB >> 19766365

Analysis of a Farquhar-von Caemmerer-Berry leaf-level photosynthetic rate model for Populus tremuloides in the context of modeling and measurement limitations.

Kathryn E Lenz1, George E Host, Kyle Roskoski, Asko Noormets, Anu Sôber, David F Karnosky.   

Abstract

The balance of mechanistic detail with mathematical simplicity contributes to the broad use of the Farquhar, von Caemmerer and Berry (FvCB) photosynthetic rate model. Here the FvCB model was coupled with a stomatal conductance model to form an [A,g(s)] model, and parameterized for mature Populus tremuloides leaves under varying CO(2) and temperature levels. Data were selected to be within typical forest light, CO(2) and temperature ranges, reducing artifacts associated with data collected at extreme values. The error between model-predicted photosynthetic rate (A) and A data was measured in three ways and found to be up to three times greater for each of two independent data sets than for a base-line evaluation using parameterization data. The evaluation methods used here apply to comparisons of model validation results among data sets varying in number and distribution of data, as well as to performance comparisons of [A,g(s)] models differing in internal-process components. 2009 Elsevier Ltd. All rights reserved.

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Year:  2009        PMID: 19766365     DOI: 10.1016/j.envpol.2009.08.004

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  1 in total

1.  A photosynthetic rate prediction model using improved RBF neural network.

Authors:  Liuru Pu; Yuanfang Li; Pan Gao; Haihui Zhang; Jin Hu
Journal:  Sci Rep       Date:  2022-06-10       Impact factor: 4.996

  1 in total

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